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Authorship verification for different languages, genres and topics
TLDR
We present a scalable authorship verification method that copes with this problem across different languages, genres and topics. Expand
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On the Usefulness of Compression Models for Authorship Verification
TLDR
We propose an intrinsic AV method, which yields competitive results compared to a number of current state-of-the-art approaches, based on support vector machines or neural networks. Expand
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Authorship Verification via k-Nearest Neighbor Estimation Notebook for PAN at CLEF 2013
TLDR
In this paper we describe our k-Nearest Neighbor (k-NN) based Au- thorship Verification method for the Author Identification (AI) task of the PAN 2013 challenge. Expand
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Authorship Verification in the Absence of Explicit Features and Thresholds
TLDR
We propose a novel parameter-free AV approach, which derives its thresholds for each verification case individually and enables AV in the absence of explicit features and training corpora. Expand
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Natural language watermarking for german texts
TLDR
In this paper we present four informed natural language watermark embedding methods, which operate on the lexical and syntactic layer of German texts. Expand
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Rethinking the Evaluation Methodology of Authorship Verification Methods
TLDR
We propose an alternative evaluation methodology based on the construction of reliable corpora in combination with a more suitable performance measure. Expand
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Authorship Verification based on Compression-Models
TLDR
We propose an intrinsic AV method, which yields competitive results compared to state-of-the-art approaches, based on support vector machines or neural networks. Expand
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Author Clustering based on Compression-based Dissimilarity Scores
TLDR
The PAN 2017 Author Clustering task examines the two application scenarios complete author clustering and authorship-link ranking. Expand
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Cross-Domain Authorship Attribution Based on Compression: Notebook for PAN at CLEF 2018
TLDR
We present a lightweight authorship attribution approach named COBAA ("Compression-Based Authorship Attribution") which is an attempt to answer this question. Expand
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An Improved Topic Masking Technique for Authorship Analysis
TLDR
We propose an effective technique called POSNoise, which aims to mask topic-related content in documents and show that it is able to outperform a well-known topic masking approach. Expand
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